University of California, Santa Cruz

About: University of California, Santa Cruz is a education organization based out in Santa Cruz, California, United States. It is known for research contribution in the topics: Galaxy & Population. The organization has 15541 authors who have published 44120 publications receiving 2759983 citations. The organization is also known as: UCSC & UC, Santa Cruz.

Using the Fisher Kernel Method to Detect Remote Protein Homologies

Abstract: A new method, called the Fisher kernel method, for detecting remote protein homologies is introduced and shown to perform well in classifying protein domains by SCOP superfamily. The method is a variant of support vector machines using a new kernel function. The kernel function is derived from a hidden Markov model. The general approach of combining generative models like HMMs with discriminative methods such as support vector machines may have applications in other areas of biosequence analysis as well.

Pore fluid constraints on the temperature and oxygen isotopic composition of the glacial ocean

Abstract: Pore fluids from the upper 60 meters of sediment 3000 meters below the surface of the tropical Atlantic indicate that the oxygen isotopic composition (δ 18 O) of seawater at this site during the last glacial maximum was 0.8 ± 0.1 per mil higher than it is today. Combined with the δ 18 O change in benthic foraminifera from this region, the elevated ratio indicates that the temperature of deep water in the tropical Atlantic Ocean was 4°C colder during the last glacial maximum. Extrapolation from this site to a global average suggests that the ice volume contribution to the change in δ 18 O of foraminifera is 1.0 per mil, which partially reconciles the foraminiferal oxygen isotope record of tropical sea surface temperatures with estimates from Barbados corals and terrestrial climate proxies.

Secure data deduplication

Abstract: As the world moves to digital storage for archival purposes, there is an increasing demand for systems that can provide secure data storage in a cost-effective manner. By identifying common chunks of data both within and between files and storing them only once, deduplication can yield cost savings by increasing the utility of a given amount of storage. Unfortunately, deduplication exploits identical content, while encryption attempts to make all content appear random; the same content encrypted with two different keys results in very different ciphertext. Thus, combining the space efficiency of deduplication with the secrecy aspects of encryption is problematic.We have developed a solution that provides both data security and space efficiency in single-server storage and distributed storage systems. Encryption keys are generated in a consistent manner from the chunk data; thus, identical chunks will always encrypt to the same ciphertext. Furthermore, the keys cannot be deduced from the encrypted chunk data. Since the information each user needs to access and decrypt the chunks that make up a file is encrypted using a key known only to the user, even a full compromise of the system cannot reveal which chunks are used by which users.